Documents published in Scipedia

• Ozone pretreatment of humid wheat straw for biofuel production

  A. jibouri, G. Turcotte, J. Wu, C. Cheng

  Energy Science & Engineering (2017).

  
  

  Abstract

  In an attempt to maximize the amount of ozone reacting with lignin inside humid wheat straw, some of the ozone-reactive lignin degradation products were washed away before a second ozonolysis delignification stage. The total contact time for the two stages was kept the same as that for a one-stage process for comparison. A significant decrease in the Acid Insoluble Lignin (AIL) content of the straw resulted: from 13.04 wt. % (after a 30-min one-stage ozonolysis) to 9.34 wt. % (after a 30-min two-stage ozonolysis, separated by a washing step). This significant improvement was accompanied by an increase in released fermentable sugars from an enzymatic hydrolysis. The yield increased from 60% theoretical sugars to 80%. A further improvement in AIL (down to 7.36 wt. %) and released sugars (up to 90% theoretical) occurred when the moisture content (MC) of the straw entering the second stage was adjusted to the optimum value of the straw entering first stage (45 wt. %, predicted from an experimental design). The authors believe this is the first time results are published for the introduction of a two-stage process separated by a washing step.

  Abstract
  In an attempt to maximize the amount of ozone reacting with lignin inside humid wheat straw, some of the ozone-reactive lignin degradation products were washed away before [...]

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• A new era of renewable power plants?

  T. Kåberger

  Energy Science & Engineering (2017).

  
  

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• Combining science and engineering for global health and prosperity

  T. Kåberger

  Energy Science & Engineering (2017).

  
  

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• Energy science during industrial transformation

  T. Kåberger

  Energy Science & Engineering (2017).

  
  

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• Capacity assessment of CO2 storage in deep saline aquifers by mineral trapping and the implications for Songliao Basin, Northeast China

  C. Jin, L. Liu, Y. Li, R. Zeng

  Energy Science & Engineering (2017).

  
  

  Abstract

  Sequestrating CO2 in deep saline aquifers is maybe the most effective option to mitigate CO2 emission. The storage capacity of CO2 is the key factor for site selection before a project is carried out. Most of the existing methods are for assessment of CO2 sequestered by stratigraphic and structural trapping, as well as residual trapping and solubility trapping. In this study, we used a new method that considers CO2 consumption through geochemical reactions with minerals of reservoir rocks, mainly sandstones. Contribution of storage capacity from carbonate mineral mainly refers to calcite is excluded. That is because lifetime of calcite (the whole time from reaction starting to calcite running out) is very short contrast with geological time-scale or it is a temporary trapping. The geochemical reactions between CO2 and feldspar minerals with thousand-year lifetime are regarded as the permanent methods for trapping CO2. CO2 consumptions by K-feldspar, albite, and anorthite are assessed with volume method based on corresponding geochemical reactions. Storage efficiency factor is also considered as one of the most important parameters in the reaction formula and it depends on specific surface area of minerals contacting with formation water and kinetics of precipitation and dissolution of minerals. We assessed the CO2 storage capacity of mineral trapping in Baokang sedimentary system, south Songliao Basin through the detailed analysis of geological data in this area. The calculated results show the total CO2 storage capacity of mineral trapping of the study area is 457.5–5114.5 Mt and the corresponding storage efficiency factor is 1%. The CO2 consumed by albite makes up more than 60% of the total storage capacity and it is about 30% for anorthite.

  Abstract
  Sequestrating CO2 in deep saline aquifers is maybe the most effective option to mitigate CO2 emission. The storage capacity of CO2 is the key factor for site selection before [...]

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• A simplified methodology for estimating solar spectral influence on photovoltaic energy yield using average photon energy

  T. Ishii, K. Otani, A. Itagaki, K. Utsunomiya

  Energy Science & Engineering (2017).

  
  

  Abstract

  Nowadays, investors, customers, and even suppliers focus on the bankability of photovoltaic (PV) technologies. However, few studies have investigated the annual net effect of solar spectrum. In this study, we estimate the net effect of the solar spectrum on the annual energy yield of c-Si and a-Si modules by two parameters. One parameter is a direct calculation from spectral factor (SF). The other parameter uses average photon energy (APE) and a regression line or curve. The estimations by the two parameters are quite consistent, whereas there is 1.2% difference between the estimations at most. Therefore, APE would be a useful index to quantify the effect of the solar spectrum.

  Abstract
  Nowadays, investors, customers, and even suppliers focus on the bankability of photovoltaic (PV) technologies. However, few studies have investigated the annual net effect [...]

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• University of Texas study underestimates national methane emissions at natural gas production sites due to instrument sensor failure

  T. Howard

  Energy Science & Engineering (2017).

  
  

  Abstract

  The University of Texas reported on a campaign to measure methane (CH4) emissions from United States natural gas (NG) production sites as part of an improved national inventory. Unfortunately, their study appears to have systematically underestimated emissions. They used the Bacharach Hi-Flow® Sampler (BHFS) which in previous studies has been shown to exhibit sensor failures leading to underreporting of NG emissions. The data reported by the University of Texas study suggest their measurements exhibit this sensor failure, as shown by the paucity of high-emitting observations when the wellhead gas composition was less than 91% CH4, where sensor failures are most likely, during follow-up testing, the BHFS used in that study indeed exhibited sensor failure consistent with under-reporting of these high emitters. Tracer ratio measurements made by the University of Texas at a subset of sites with low CH4 content further indicate that the BHFS measurements at these sites were too low by factors of three to five. Over 98% of the CH4 inventory calculated from their own data and 41% of their compiled national inventory may be affected by this measurement failure. Their data also indicate that this sensor failure could occur at NG compositions as high as 97% CH4, possibly affecting other BHFS measurement programs throughout the entire NG supply chain, including at transmission sites where the BHFS is used to report greenhouse gas emissions to the United States Environmental Protection Agency Greenhouse Gas Reporting Program (USEPA GHGRP, U.S. 40 CFR Part 98, Subpart W). The presence of such an obvious problem in this high profile, landmark study highlights the need for increased quality assurance in all greenhouse gas measurement programs.

  Abstract
  The University of Texas reported on a campaign to measure methane (CH4) emissions from United States natural gas (NG) production sites as part of an improved national inventory. [...]

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• Greenhouse gas emissions from domestic hot water: heat pumps compared to most commonly used systems

  B. Hong, R. Howarth

  Energy Science & Engineering (2017).

  
  

  Abstract

  We estimate the emissions of the two most important greenhouse gasses (GHG), carbon dioxide (CO2) and methane (CH4), from the use of modern high-efficiency heat pump water heaters compared to the most commonly used domestic hot water systems: natural gas storage tanks, tankless natural gas demand heaters, electric resistance storage tanks, and tankless electric resistance heaters. We considered both natural gas-powered electric plants and coal-powered plants as the source of the electricity for the heat pumps, the thermal electric storage tanks, and the tankless electric demand heaters. The time-integrated radiative forcing associated with using a heat pump water heater was always smaller than any other means of heating water considered in this study across all time frames including at 20 and 100 years. The estimated amount of CH4 lost during its lifecycle was the most critical factor determining the relative magnitude of the climatic impact. The greatest net climatic benefit within the 20-year time frame was predicted to be achieved when a storage natural gas water heater (the most common system for domestic hot water in the United States) fueled by shale gas was replaced with a high efficiency heat pump water heater powered by coal-generated electricity, the heat pump system powered by renewable electricity would have had an even greater climatic benefit, but was not explicitly modeled in this study. Our analysis provides the first assessment of the GHG footprint associated with using a heat pump water heater, which we demonstrate to be an effective and economically viable way of reducing emissions of GHGs.

  Abstract
  We estimate the emissions of the two most important greenhouse gasses (GHG), carbon dioxide (CO2) and methane (CH4), from the use of modern high-efficiency heat pump water [...]

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• Parametric analysis and systems design of dynamic photovoltaic shading modules

  J. Hofer, A. Groenewolt, P. Jayathissa, Z. Nagy, A. Schlueter

  Energy Science & Engineering (2017).

  
  

  Abstract

  Shading systems improve building energy performance and occupant comfort by controlling glare, natural lighting, and solar gain. Integrating PV (photovoltaics) in shading systems opens new opportunities for BIPV (building integrated photovoltaics) on façades. A key problem of such systems is mutual shading among PV modules as it can lead to electrical mismatch losses and overheating effects. In this work, we present a new modeling framework, which couples parametric 3D with high-resolution electrical modeling of thin-film PV modules to simulate electric energy yield of geometrically complex PV applications. The developed method is able to predict the shading pattern for individual PV modules with high spatio-temporal resolution, which is of great importance for electrical system design. The methodology is applied to evaluate the performance of different dynamic BIPV shading system configurations, as well as its sensitivity to façade orientation and module arrangement. The analysis shows, that there is a trade-off between tracking performance and mutual shading of modules. Distance between modules is a critical parameter influencing the amount of mutual shading and hence limiting solar irradiation and electricity generation of PV shading systems using solar tracking. Planning of module string configuration, PV cell orientation, and location of bypass diodes according to partial shading conditions, reduces electrical mismatch losses and results in significantly higher electricity generation. The integration of parametric 3D and electrical modeling opens new possibilities for PV system design and dynamic control optimization. Though the analysis focuses on BIPV, the method is useful for the planning and operation of solar tracking systems in general.

  Abstract
  Shading systems improve building energy performance and occupant comfort by controlling glare, natural lighting, and solar gain. Integrating PV (photovoltaics) in shading [...]

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• Automatized analysis of IR-images of photovoltaic modules and its use for quality control of solar cells

  J. Hepp, F. Machui, H. Egelhaaf, C. Brabec, A. Vetter

  Energy Science & Engineering (2017).

  
  

  Abstract

  It is well known that the performance of solar cells may significantly suffer from local electric defects. Accordingly, infrared thermography (i.p. lock-in thermography) has been intensely applied to identify such defects as hot spots. As an imaging method, this is a fast way of module characterization. However, imaging leads to a huge amount of data, which needs to be investigated. An automatized image analysis would be a very beneficial tool but has not been suggested so far for lock-in thermography images. In this manuscript, we describe such an automatized analysis of solar cells. We first established a robust algorithm for segmentation (or recognition) for both, the PV-module and the defects (hot spots). With this information, we then calculated a parameter from the IR-images, which could be well correlated with the maximal power (Pmpp) of the modules. The proposed automatized method serves as a very useful foundation for faster and more thorough analyses of IR-images and stimulates the further development of quality control on solar modules.

  Abstract
  It is well known that the performance of solar cells may significantly suffer from local electric defects. Accordingly, infrared thermography (i.p. lock-in thermography) has [...]

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